Influence of electromechanical effects and wetting layers on band structures of AlN/GaN quantum dots and spin control
Bibliographic record
Abstract
In a series of recent papers we demonstrated that coupled electromechanical effects can lead to pronounced contributions in band structure calculations of low dimensional semiconductor nanostructures (LDSNs) such as quantum dots (QDs), wires, and even wells. Some such effects are essentially nonlinear. Both strain and piezoelectric effects have been used as tuning parameters for the optical response of LDSNs in photonics, band gap engineering, and other applications. However, the influence of spin orbit effects in presence of external magnetic field on single and vertically coupled QD has been largely neglected in the literature. The electron spin splitting terms which are coupled to the magnetic field through the Pauli spin matrix in these QDs become important in the design of optoelectronic devices as well as in tailoring properties of QDs in other applications areas. At the same time, single and vertically stacked QDs are coupled with electromagnetic and mechanical fields which become increasingly important in many applications of LDSN-based systems, in particular, where spin splitting energy is important. These externally applied electric and magnetic fields as well as the separation between the vertically coupled QDs can be used as tuning parameters. Indeed, as electromagnetic and elastic effects are often significant in LDSNs, it is reasonable to expect that the externally applied magnetic fields oriented along a direction perpendicular to the plane of two-dimensional electron gas in the QDs may also be used as a tuning parameter in the application of light emitting diodes, logic devices, for example, OR gates, AND gates and others. In this paper, by using the fully coupled model of electroelasticity, we analyze the influence of these effects on optoelectronic properties of QDs. Results are reported for III–V type semiconductors with a major focus given to AlN/GaN based QD systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".